Leadership as Accountability for Learning: The Effects of School Poverty, Teacher Experience, Previous Achievement, and Principal Preparation Programs on Student Achievement

Abstract

In the current era of accountability for achievement, school principals play the pivotal role of instructional leader. In a high-stakes testing environment, leadership preparation programs in universities and school districts need to be positively related to academic outcomes. The purpose of this study was to examine the relationship between school leadership preparation programs and student achievement in urban settings. Because leadership is contingent on the setting, school contextual factors and their impact on student achievement framed this study. Regression techniques were employed to construct a conceptual model with predictors of criterion and norm-referenced student achievement scores. Confirming previous research findings, student poverty, teacher experience, and previous achievement were the strongest predictors and accounted for a significant amount of variance in student achievement; however, university and district preparation programs were not significant predictors. Implications for policy, practice, and future research are discussed.

Comparison of Self-Contained and Departmentalized Elementary Teachers' Perceptions of Classroom Structure and Job Satisfaction

“…Teacher retention was shown to have significant positive impacts on student achievement (Barmby, 2006;Vanderhaar, Mu, & Rodosky, 2006). Vanderhaar et al (2006) found teachers' average years of teaching, along with student poverty level and previous testing achievement, were the best indicators of student achievement. To keep teachers in the field longer and increase their average years of experience, school officials should advocate practices that prevent teacher burnout.…”

Examining teachers' perceptions of psychological gender and leadership behavior of principals in public elementary schools.

“…(2003) found substantial relationships between school leadership and student achievement, citing previous revealing effect sizes as large as 0.50. Vanderhaar, Munoz, and Rodosky (2006) determined that principals playa pivotal role in transforming and shaping student achievement. Further research employing student achievement measures could illustrate the role that the psychological gender-leadership relationship plays in school success.…”

Diversity for diversity's sake? The relationship between diversity and school-level academic achievement.

“…Moreover, a growing body of literature on the relationship between academic achievement and the concentration of poverty within a school has demonstrated that the effects of high concentrations of poverty often extend beyond the effects of an individual's poverty (Banks, 2001;Orfield & Lee, 2005;Vanderhaar, Muñoz, & Rodosky, 2006). Many studies operationalize collective SES using single variables, such as residing in social housing (Martens et al, 2014) or by simply asking principals what percentage of their students were of low SES, average SES, or high SES and then calculating a heterogeneity index similar to the Blau index of racial diversity or Simpson's index (1949) in ecological studies (Menzer & Torney-Purta, 2012) while others use a combination of multiple and varied factors.…”

“…This trend suggests a possible limitation of the present study since intra-school tracking may further confound the results; however, it should be noted that the present study seeks to inform student school-assignment in districts with high geographic stratification of SES and cannot control for within-school tracking. Finally, covariates omitted to control for extraneous exogenous or endogenous effects, notably student priorachievement (e.g., Vanderhaar et al, 2006), run the risk of potential omitted variables bias, which can lead to overestimating the effects of peer SES. The present study takes into account prior student achievement by examining measures of student growth and controls for endogenous, school-level process variables while omitting school input variables which are highly correlated to the DI in an effort to mitigate the risk of multicollinearity.…”

“…Other studies have utilized regression discontinuity approaches (Vardardottir, 2013), meta-analytic approaches (Ewijk & Sleegers, 2010) and multivariate latent growth curve analysis (Hornstra et al, 2015). Approaches to constructing these models have varied widely and include exploratory (Vanderhaar et al, 2006) and theoretically-based (Carman & Zhang, 2011) models.…”